Abstract
In recent years there has been a major development in optical communications and a new generation of fibers was introduced. These fibers, called Photonic Crystal Fibers (PCF) have unusual propagation properties. This paper presents multicriteria PCF design tool, which is an accurate PCF design based on multicriteria classification. This method combines the deductive and the inductive learning and it is introduced for the first time in the field of optical fibers. The multicriteria decision analysis (MCDA) makes it possible to evaluate the optical proprieties of PCFs by determining the resemblance of a PCF fiber to specified PCF category. The MCDA avoids recourse to classical distances and makes it possible to use quantitative and/or qualitative criteria. Moreover, it defeats some difficulties encountered when data are expressed in different units. These advantages allow the new multicriteria classification method to be employed easily to the diagnosis and to the design of photonic-crystals fibers.